Sham Kakade, professor in the Department of Statistics and the Allen School of Computer Science and Statistics Professor Zaid Harchaoui have secured a $1.5 million award from the National Science Foundation (NSF) to develop new algorithmic tools that will advance the state of the art in data science. The funding will support the researchers’ project titled “Algorithms for Data Science: Complexity, Scalability, and Robustness” as part of the agency’s Transdisciplinary Research in Principles of Data Science (TRIPODS) program.
TRIPODS was designed to engage members of the theoretical computer science, mathematics and statistics communities in developing the theoretical foundations of data science to promote data-driven discovery. The UW proposal aims to produce a common language and set of design principles to guide the development of new algorithmic tools that will automate the process of extracting robust insights from vast troves of data.
“Modern data science challenges transcend the ideas of any single discipline, which is what makes this work so exciting,” Kakade said. “With the growing availability of large datasets and increasing computational resources, we need more robust algorithmic tools to address contemporary data science challenges — and we believe a unifying approach is needed to overcome those challenges, accelerate the pace of scientific discovery and generate solutions to real-world problems.”
In addition to developing the language for data-driven discovery, the researchers intend to train students and postdoctoral scholars to be well-versed in the disciplines that underpin data science and incorporate theoretical ideas into a data science curriculum.
(Originally published in Allen School News)